Rewards Analytics and Distribution Dashboard

This goal of this notebook is to offer an easy way to process the outputs of the praise and sourcecred reward systems, perform an analysis of the results and calculate the token reward distribution. It uses mock data and should be considered a work-in-progress.

Imports

First, we import the relevant libraries, get the Data and set how many tokens we want to distribute

Now that we have selected the files, we can import them for processing. We can also set the total amount of tokens we want to distribute this period. We also set the name we want our output file to have.

Tip: Now that the file paths are set, you can safely click on "Cell > Run all below" from here on the menu bar to execute everything :)

Parameters

Set the total amount of tokens we want to distribute this period. We also set the name we want our output file to have.

Results Analysis

Let's dive into some data analysis! We'll use the metrics designed and explained by octopus🐙, and focus only on the praise rewards for now. Starting with:

Allocation percentages - Praise receivers

This table will show us which percentage of the total rewards gets distributed to which top % of users. So "Top 50% -> 0.85" would mean that the top 50% of praisees received 85% of the total rewards

	Rewards
Top 50%	0.967166
Top 20%	0.793193
Top 10%	0.553922
Top 5%	0.330281
Top 1%	0.120977

Allocation Percentages - Praise givers

This table will show us which percentage of the total rewards get distributed based on praise given by which top % of users. So "Top 50% -> 0.85" would mean that 85% of the total rewards are based on praise given by the top 50% praise givers.

	Rewards
Top 50%	0.966611
Top 20%	0.814650
Top 10%	0.713559
Top 5%	0.644932
Top 1%	0.420459

Plotting praise given against praise received

Now we can compare the relationship between praise given by a user and the praise they received

Gini coefficient

Next we will look at the Gini coefficient. Note that there is some debate if we want to use this metric at all, since it is usually employed to measure wealth distribution, and not compensation.

	Rewards
All	0.733363
Top 50%	0.547062
Top 20%	0.254984

Shannon Entropy

Shannon Entropy) is a concept from communications theory, which is also used in measuring the diversity of a distribution. The formula for calculating Shannon Entropy among $n$ individuals is $$\\sum_{k=1}^n -p_k log_2(p_k),$$ where $p_k$ represents the proportion of the resource that user $k$ received.

Here we compare the actual Shannon Entropy with the maximum possible for the dataset, keeping in mind that a Shannon Entropy of 0 would mean one user holds all the rewards

	Rewards
Entropy	5.584338
Max Entropy	7.066089
% of Max	0.790301

Nakamoto Coefficient

Last but not least, the Nakamoto coefficient. The Nakamato Coefficient is defined as the smallest number of accounts who control at least 50% of the resource. Although its significance relates to the prospect of a 51% attack on a network, which may not be relevant in our context, we can still use it as an intuitive measure of how many individuals received the majority of a resource.

13

Praise Data Visualization

Rating distribution

Since praise gets valued on a scale, we can take a look at how often each value of the scale gets assigned by quantifiers.

Praise Reward Distribution

We can also take a look at the distribution of the received praise rewards

Praise Outliers

To aid the revision process, we can generate a table which sorts the praise by the size of the spread between the highest and lowest scores. These "controversial" praise instances can then be discussed in the quantifier review call. Index numbers are kept to make localization in the "big praise sheet" easier.

	index	ID	DATE	TO USER ACCOUNT	FROM USER ACCOUNT	REASON	SCORE 1	SCORE 2	SCORE 3	SCORE 4	...	QUANTIFIER 2 USERNAME	QUANTIFIER 3 USERNAME	QUANTIFIER 4 USERNAME	QUANTIFIER 4 ETH ADDRESS	AVG SCORE	CORRECTION ADD	CORRECTION SUB	CORRECTION COMMENT	FINAL QUANT	SPREAD
0	441	621f79e243b89009366c94cb	2021-10-07T22:00:00.000Z	Juankbell#7458	iviangita#3204	for putting on all the Graviton curriculum tog...	13	1	144	8	...	divine_comedian#5493	bear100#9085	osycross(🦎🦎)#5943	0xFe99402763531258875949D449db20157b77Ec5C	41	NaN	NaN	NaN	41	143
1	1561	621f79e343b89009366c9999	2021-10-28T22:00:00.000Z	akrtws (TE Academy)#4246	iviangita#3204	for the success of Token Engineering Academy	144	144	8	34	...	Parrachia#0450	Nuggan#5183	Vyvy-vi#5040	0x2fA130927814B590623031e846f059df9554FdDe	82	NaN	NaN	NaN	82	136
2	661	621f79e243b89009366c95ac	2021-10-09T22:00:00.000Z	divine_comedian#5493	griff (💜, 💜)#8888	for working on Sunday in the Params hack sesh ...	89	0	13	0	...	Parrachia#0450	lee0007#8152	Vyvy-vi#5040	0x2fA130927814B590623031e846f059df9554FdDe	51	NaN	NaN	NaN	51	89
3	494	621f79e243b89009366c9500	2021-10-07T22:00:00.000Z	Nuggan#5183	iviangita#3204	for all the work they do in the Params WG: des...	34	21	89	21	...	Maxwe11#7157	bear100#9085	osycross(🦎🦎)#5943	0xFe99402763531258875949D449db20157b77Ec5C	41	NaN	NaN	NaN	41	68
4	1564	621f79e343b89009366c999c	2021-10-28T22:00:00.000Z	r33pich33p#6906	iviangita#3204	for being productive and engaging with Eduardo...	0	5	55	5	...	tigeroid#2951	shawn#7046	enti#1546	0x6897aBe0fD62B589260784B21F4ca3F78A0D8017	21	NaN	NaN	NaN	21	55
5	178	621f79e243b89009366c93ba	2021-10-01T22:00:00.000Z	Juankbell#7458	Mount Manu#3530	for the 2nd Graviton training 🧑🏻‍🚀	13	0	55	0	...	divine_comedian#5493	bear100#9085	osycross(🦎🦎)#5943	0xFe99402763531258875949D449db20157b77Ec5C	17	NaN	NaN	NaN	17	55
6	1169	621f79e343b89009366c97f6	2021-10-21T22:00:00.000Z	eduardovegap#0422	Mount Manu#3530	for their amazing Communitas work around resea...	55	13	0	5	...	Maxwe11#7157	shawn#7046	enti#1546	0x6897aBe0fD62B589260784B21F4ca3F78A0D8017	18	NaN	NaN	NaN	18	55
7	1189	621f79e343b89009366c980a	2021-10-21T22:00:00.000Z	markop#2007	Mount Manu#3530	for all their work and dedication towards the ...	0	55	8	0	...	Maxwe11#7157	Nuggan#5183	enti#1546	0x6897aBe0fD62B589260784B21F4ca3F78A0D8017	21	NaN	NaN	NaN	21	55
8	1529	621f79e343b89009366c9979	2021-10-28T22:00:00.000Z	chuygarcia.eth#6692	iviangita#3204	for the infinite contributions they brought an...	0	55	8	21	...	Parrachia#0450	lee0007#8152	Mike Brunt#0745	0x457Ea659aAAbD496550264c6d9d6351666f2fB4b	28	NaN	NaN	NaN	28	55
9	1516	621f79e343b89009366c996c	2021-10-28T22:00:00.000Z	markop#2007	iviangita#3204	for doing the AMA on the dashboard at Commons ...	0	55	8	5	...	Maxwe11#7157	Nuggan#5183	enti#1546	0x6897aBe0fD62B589260784B21F4ca3F78A0D8017	22	NaN	NaN	NaN	22	55
10	909	621f79e243b89009366c96a5	2021-10-14T22:00:00.000Z	markop#2007	iviangita#3204	for their awesome work in the last weeks on th...	0	55	8	0	...	Maxwe11#7157	Nuggan#5183	enti#1546	0x6897aBe0fD62B589260784B21F4ca3F78A0D8017	21	NaN	NaN	NaN	21	55
11	14	621f79e243b89009366c930e	2021-09-30T22:00:00.000Z	markop#2007	iviangita#3204	for their support in the dashboard app	0	55	0	13	...	Maxwe11#7157	Nuggan#5183	enti#1546	0x6897aBe0fD62B589260784B21F4ca3F78A0D8017	23	NaN	NaN	NaN	23	55
12	495	621f79e243b89009366c9501	2021-10-07T22:00:00.000Z	divine_comedian#5493	iviangita#3204	for all the work they do in the Params WG: des...	55	0	13	0	...	Parrachia#0450	lee0007#8152	Vyvy-vi#5040	0x2fA130927814B590623031e846f059df9554FdDe	34	NaN	NaN	NaN	34	55
13	168	621f79e243b89009366c93b0	2021-10-01T22:00:00.000Z	liviade#1387	Mount Manu#3530	for all the work that she does in the community 🤗	13	1	55	5	...	Mettodo#7010	Zeptimus#3359	eduardovegap#0422	0x1d921dff757610FbDB0073479e12c0a07d382677	18	NaN	NaN	NaN	18	54
14	1255	621f79e343b89009366c984c	2021-10-22T22:00:00.000Z	pKrepe#5682	Mount Manu#3530	for their hard development work in the CCD	2	2	55	144	...	Parrachia#0450	kristofer#1475	Vyvy-vi#5040	0x2fA130927814B590623031e846f059df9554FdDe	50	NaN	NaN	NaN	50	53
15	649	621f79e243b89009366c95a0	2021-10-08T22:00:00.000Z	MsMagey#8357	ALOYSIOUS#3049	for her dedication to learning with the gravit...	55	3	13	8	...	Tam2140#9361	shawn#7046	eduardovegap#0422	0x1d921dff757610FbDB0073479e12c0a07d382677	19	NaN	NaN	NaN	19	52
16	1352	621f79e343b89009366c98ad	2021-10-25T22:00:00.000Z	RodriCastillo#1415	chuygarcia.eth#6692	for his amazing designs for Params Parties, wh...	21	3	55	21	...	Tam2140#9361	bear100#9085	bends#3537	0x1E975f53956d644868F3eA25690b1bbEda658565	25	NaN	NaN	NaN	25	52
17	1252	621f79e343b89009366c9849	2021-10-22T22:00:00.000Z	Vitor Marthendal#0090	Mount Manu#3530	for their hard development work in the CCD	3	5	55	8	...	Mettodo#7010	kristofer#1475	eduardovegap#0422	0x1d921dff757610FbDB0073479e12c0a07d382677	17	NaN	NaN	NaN	17	52
18	501	621f79e243b89009366c9507	2021-10-07T22:00:00.000Z	akrtws (TE Academy)#4246	iviangita#3204	for the support Livia feels in your presence a...	5	55	8	5	...	Parrachia#0450	Nuggan#5183	Vyvy-vi#5040	0x2fA130927814B590623031e846f059df9554FdDe	18	NaN	NaN	NaN	18	50
19	1360	621f79e343b89009366c98b8	2021-10-26T22:00:00.000Z	sem 🐝#0161	liviade#1387	for spotting a mistake on Gitbook and being pr...	13	5	55	5	...	Tam2140#9361	shawn#7046	bends#3537	0x1E975f53956d644868F3eA25690b1bbEda658565	19	NaN	NaN	NaN	19	50
20	765	621f79e243b89009366c9615	2021-10-13T22:00:00.000Z	Vitor Marthendal#0090	divine_comedian#5493	for development on the CCD	21	5	55	13	...	Mettodo#7010	kristofer#1475	eduardovegap#0422	0x1d921dff757610FbDB0073479e12c0a07d382677	23	NaN	NaN	NaN	23	50
21	1562	621f79e343b89009366c999a	2021-10-28T22:00:00.000Z	solsista#5370	iviangita#3204	for being our ethics guardian	5	55	5	13	...	Parrachia#0450	lee0007#8152	osycross(🦎🦎)#5943	0xFe99402763531258875949D449db20157b77Ec5C	19	NaN	NaN	NaN	19	50
22	1178	621f79e343b89009366c97ff	2021-10-21T22:00:00.000Z	liviade#1387	Mount Manu#3530	for her leadership in governance & in Soft Gov	13	5	55	8	...	Mettodo#7010	Zeptimus#3359	eduardovegap#0422	0x1d921dff757610FbDB0073479e12c0a07d382677	20	NaN	NaN	NaN	20	50
23	266	621f79e243b89009366c9412	2021-10-01T22:00:00.000Z	karmaticacid#1218	Mount Manu#3530	for their leadership🧙🏻 🧙🏻‍♂️ 🧙🏻‍♀️	21	55	5	5	...	Parrachia#0450	bear100#9085	eduardovegap#0422	0x1d921dff757610FbDB0073479e12c0a07d382677	21	NaN	NaN	NaN	21	50
24	1549	621f79e343b89009366c998d	2021-10-28T22:00:00.000Z	karmaticacid#1218	iviangita#3204	for working on something that makes everyone i...	8	55	5	13	...	Parrachia#0450	bear100#9085	eduardovegap#0422	0x1d921dff757610FbDB0073479e12c0a07d382677	20	NaN	NaN	NaN	20	50

25 rows × 29 columns

We can also plot the spread against the average score for a more visual search.
ATTENTION! Keep in mind that this is just meant as a visual aid. If there are several praise instances with similar spread and average quant number, all but one end up "hidden" on the chart. For the full list you have to use the table.

Praise Flows

Now for something more fun: let's surface the top "praise flows" from the data. Thanks to @inventandchill for this awesome visualization! On one side we have the top 20 praise givers separately (modifiable by changing the variable n_senders), on the other the top 25 receivers (modifiable by changing the variable n_receivers). The people outside the selection get aggregated into the "REST FROM" and "REST TO" categories.

SourceCred Data

SourceCred token Distribution

Next we can see the distribution made by the SourceCred algorithm.

Quantifier Data

Let's take a closer look at each quantifier. In the following step we will use the raw praise data to zoom in on how each quantifier scored the praises:

Amount of praise quantified

With the above table we can easily see how much praise each quantifier rated.

Mean praise score by quantifier

Let's see the mean praise scores every quantifier gave.

Total Token Distribution Visualization and Export

To send the allocations to the DAO for distribution, we need to put all data together and add the rewards for the reward board and the quantifiers.

Let's take a final look at the total distribution. Click on the legend to filter out specific reward sources

That's it! We can now download the final distribution files and upload them to GitHub for future reference. We want to export 3 different files:
 - The final reward allocations, separated by source
 - The final reward allocations, in a disperse.app-readable format
 - The extended praise data, detailing the how many tokens each single praise netted (for future reference)